以往，大众媒体主要通过民意调查来量化民意；如今，微博热搜日益被视为民意的风向标。本文应用民意基础设施模型，采用文本分析、访谈和内容分析法，考察热搜定义和测量民意的方式，以及大众媒体如何看待和阐释热搜。研究发现，随着2018年上榜规则的调整，热搜糅合了“个体的搜索痕迹聚合”和“公众之间的互动和交流”，前者是个体的、私下的、平等的，后者是关系的、公开的、分层级的，标志着“一人一票”逻辑向“优先考虑明智舆论”的转变。媒体将热搜描绘为民意的代名词，常使用“冲上热搜”“热搜第一”作为评估公众反应的基准，进而合法化了热点算法的知识逻辑。该发现有助于修正“党媒对算法持批判态度”的结论，未来研究可纳入更多“人与算法相遇”的具体场景。

Mass media used to quantify public opinion through poll survey; nowadays, Weibo Hot Search has increasingly been considered as the barometer of public opinion. Drawing on the public opinion infrastructures model, this article uses the methods of text analysis, interview, and content analysis to investigate how Hot Search defines and measures public opinion and how it is framed and interpreted by the mass media. We find that Hot Search had combined “the aggregation of scattered individuals’ search traces” and “the engagement and communication between the publics” since the adjustment of the trending rules in 2018. While the former is individual, private, and egalitarian, the latter is relational, public, and hierarchical. This signifies a shift in logic from “one person, one vote” to “wise public opinion prioritized”. The media frames Hot Search as the synonym of public opinion, with the terms “rocketed to” and “top one” most frequently used as the benchmarks to evaluate the public response, thus legitimizing the knowledge logic of trending algorithms. This finding contributes to revising the previous conclusion, which held that “the party media held a critical attitude towards algorithms”. The future research could take more concrete contexts where “people and algorithms meet” into account.